On a multivariate gamma distribution

A multivariate probability model possessing a dependence structure that is reflected in its variance–covariance structure and gamma distributed univariate margins is introduced and studied. In particular, the higher order moments and cumulants, Chebyshev-type inequalities and multivariate probability density functions are derived. The model suggested herein is believed to be capable of describing dependent insurance losses.